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A Platform for Free-Weight Exercise Monitoring with Passive Tags

  • Han Ding
  • , Jinsong Han
  • , Longfei Shangguan
  • , Wei Xi
  • , Zhiping Jiang
  • , Zheng Yang
  • , Zimu Zhou
  • , Panlong Yang
  • , Jizhong Zhao
  • Xi'an Jiaotong University
  • Princeton University
  • Tsinghua University
  • Swiss Federal Institute of Technology Zurich
  • PLA University of Science and Technology

科研成果: 期刊稿件文章同行评审

65 引用 (Scopus)

摘要

Regular free-weight exercise helps to strengthen natural movements and stabilize muscles that are important to strength, balance, and posture of human beings. Prior works have exploited wearable sensors or RF signal changes for activity sensing, recognition, and counting, etc.. However, none of them have incorporated three key factors necessary for a practical free-weight exercise monitoring system: recognizing free-weight activities on site, assessing their qualities, and providing useful feedbacks to the bodybuilder promptly. Our FEMO system provides an integrated free-weight exercise monitoring service that incorporates all the essential functionalities mentioned above. FEMO achieves this by attaching passive RFID tags on the dumbbells and leveraging the Doppler shift profile of the reflected backscatter signals for on-site free-weight activity recognition and assessment. The rationale behind FEMO is 1) since each free-weight activity owns unique arm motions, the corresponding Doppler shift profile should be distinguishable to each other. 2) Doppler profile of each activity has a strong spatial-temporal correlation that implicitly reflects the quality of the activity. We implement FEMO with COTS RFID devices and conduct a two-week experiment. The preliminary result from 15 volunteers demonstrates that FEMO can be applied to a variety of free-weight activities, and provide valuable feedbacks for activity alignment.

源语言英语
文章编号7893704
页(从-至)3279-3293
页数15
期刊IEEE Transactions on Mobile Computing
16
12
DOI
出版状态已出版 - 1 12月 2017

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